Feature binding as neuron synchronization: quantum aspects

Abstract

Feature binding denotes how a large collection of coupled neurons combines external signals with internal memories into new coherent patterns of meaning. An external stimulus spreads over an assembly of coupled neurons, building up a corresponding collective state. Thus, the synchronization of spike trains of many individual neurons is the basis of a coherent perception.Homoclinic chaos has been proposed as the most suitable way to code information in time by trains of equal spikes occurring at apparently erratic times; a new quantitative indicator, called propensity, is introduced to select the most appropriate neuron model.In order to classify the set of different perceptions, the percept space is given a metric structure. The distance in percept space is conjugate to the duration of the perception in the sense that an uncertainty relation in percept space is associated with time limited perceptions. Thus coding of different percepts by synchronized spike trains entails fundamental quantum features with a quantum constant related to the details of the perceptual chain and very different from Planck's action. I. FEATURE BINDING A. Neuron synchronizationIt is by now established that a holistic perception emerges, out of separate stimuli entering different receptive fields, by synchronizing the corresponding spike trains of neural action potentials [1,2].Action potentials play a crucial role for communication between neurons. They are steep variations in the electric potential across a cell's membrane, and they propagate in essentially constant shape from the soma (neuron's body) along axons toward synaptic connections with other neurons. At the synapses they release an amount of neurotransmitter molecules depending upon the temporal sequences of spikes, thus transforming the electrical into a chemical carrier.As a fact, neural communication is based on a temporal code whereby different cortical areas which have to contribute to the same percept P synchronize their spikes. Limiting for convenience the discussion to the visual system, spike emission in a single neuron of the higher cortical regions results as a trade-off between bottom-up stimuli arriving through the LGN (lateral geniculate nucleus) from the retinal detectors and threshold modulation due to top-down signals sent as conjectures by the semantic memory. This is the core of ART (adaptive resonance theory [3]) or other computational models of perception [4] which assume that a stable cortical pattern is the result of a Darwinian competition among different percepts with different strength. The winning pattern must be confirmed by some matching procedure between bottom-up and top-down signals.

Quantum cognition based on an ambiguous representation derived from a rough set approximation

“…A particular motor decision emerges from the processing unit's global work space where the choice among competing signals arriving to it takes place. In some hypothesis, global work space acts as a threshold system by which the winner of competing neural groups is chosen [33][34]45]. That is verified by evidence where the largest synchronized domain has occurred with each interpretation.…”

“…Based on such an approach Arrechi and his team conjecture and offer estimations for the existence of a quantal constant (Note: This is not the standard Plank constant of quantum physics but rather a quantum-like constant in the spirit of quantal neuron discharge proposed by Katz [31]) underlying specific quantum-like information processing for visual stimuli. As Arecchi demonstrates [32][33][34] the operation of the observing apparatus is equivalent to the operation of monitoring a Wigner distribution. The reported time coding implies a Wigner non-local measurement that stores and reads data in a global rather than a serial local fashion.…”